Two effectors

• Knocked out independently
• Host chlorosis measured

Communication

• Stories told through figures

Scales matter

• Indication of quantities

Context matters

• The same or not the same?

Storytelling

• Figures are what you remember of a ‘story’

• What about uncertainty?

Four effectors

• Bacterial effectors
• Inoculate wild-type plants
• Measure growth (CFU)

Four bar plots

• Do the effectors have the same effect?

Add error bars

• Do the effectors have the same effect?

Error bars

• Estimates of uncertainty
• But uncertainty of what?
• standard deviation (sd):
  • describes the data: how much members of the group differ from the mean
• standard error (of the mean) (sem):
  • describes the estimate of the mean: standard deviation of the estimate of the mean

SD or SEM?

• Which was used (& which do you need to know)?

Raw data

• Are they the same biological responses?

What does mean mean?

• Same mean implies the same response?

What does mean mean?

• Unequal sample sizes (cf. barplot)

What does mean mean?

• Outliers (cf. barplot)

What does mean mean?

• Bimodal distribution (cf. barplot)

We only use figures as guides…

• “Figures tell a story, but we actually only believe the stats”
• Typical paper:
  • P<0.05, t-test (NHST), a description if you’re lucky
• Do the distributions support use of a t-test, e.g. assumptions for 2-sample t-test:
  • both populations Normal
  • equal standard deviations

…we trust the P-values

• Bar plots can hide inappropriate assumptions

Source: Weissgerber et al. (2015)

Figures can mislead

• reinforce poor practice
  • binary thinking
  • overlooking data distributions and wrong statistical assumptions for tests
  • overlooking uncertainty
• suggest neat stories (P<0.05)
  • data, like life, can be messy

Your analysis?

• What you did…
  • Open package foo. Click. Click, drag. Click, Click. Undo. Click. Right-click. Save results.csv
  • Load into Excel. Click, drag. Generate graph. Right-click. Save pretty-graph.png

Your analysis?

• What you said you did in the paper…
  • I analysed my data in foo using the bar analysis. Results are shown in Figure 1.

How reproducible is a mouse click?

Reproducible research

• Automate (i.e. learn to program)
• Write code in a (very) high-level language
• Get some training
• Use version control
• Get a code buddy
• Share code and data openly
• Write tests

Now what?

• “Thanks for undermining me. Now what do I do about it?”
• Other data representations are available (UseR!)
• Data visualisation/statistics/programming training courses
  • Research Data Visualisation Workshops
  • Data Carpentry
  • Software Carpentry

Anscombe’s Quartet

• Four datasets: same means and standard deviations

Boxplots

• Median, interquartiles, outliers

Raw data

• 1D scatterplots

Box and raw data

• Boxplots and jittered 1D scatterplots

Violin plot

• Data density estimate

Violin and raw data

• Stacked, not jittered, data

Where do ideas come from?

• Christina Bergmann: “Visualization in Biology or Why #barbarplots”
  • most of this presentation: RDVW presentation
  • #barbarplots
• Mike Croucher: “Is Your Research Software Correct?”
  • most of the rest of this presentation: Presentation
• Software Carpentry
• Data Carpentry
• Software Sustainability Institute

References

Anscombe, F. J. (1973). “Graphs in Statistical Analysis.” American Statistician 27 (1): 17–21. pp. 17-21. Paper

Weissgerber, T. L. et al. (2015). “Beyond bar and line graphs: Time for a new data presentation paradigm.” PLoS Biology, 13(4), e1002128. doi:10.1371/journal.pbio.1002128 Paper